When text is translated from one language into another, sentiment is preserved to varying degrees. In this paper, we use Arabic social media posts as stand-in for source language text, and determine loss in sentiment predictability when they are translated into English, manually and automatically. As benchmarks, we use manually and automatically determined sentiment labels of the Arabic texts. ...

SYSTRAN started the design and the development of Arabic, Farsi and Urdu to English machine translation systems in July 2002. This paper describes the methodology and implementation adopted for dictionary building and morphological analysis. SYSTRAN’s IntuitiveCoding® technology (ICT) facilitates the creation, update, and maintenance of Arabic, Farsi and Urdu lexical entries, is more modular an...

The paper defines corpus-based machine translation and its possible applications in machine translation. The study is based on a bilingual corpus of French and Arabic texts and translation unit alignment. The criteria used for alignment combine linguistic and statistical information. The study also suggests procedures to build a machine translation system based on parallel translated corpora.

Translation learning must be able to develop students' translation competence. One alternative model that can developed is a with an eco-translatology perspective which further optimizes the ecological environment of and student autonomy as learners. This study aims determine needs for developing models, especially Arabic-Indonesian translation, using perspective. The method applied survey inst...

OBJECTIVE To translate into Arabic and validate the SF-36 quality of life index in a Tunisian Arabic population. BACKGROUND No validated Arabic quality of life index is published. DESIGN Arabic translation of the SF-36 scale was obtained by the "forward/backward translation" method. Adaptations were made after a pilot study involving 22 subjects from general population. Inter-rater reliabil...

Machine translation engines draw on various types of databases. This paper is concerned with Arabic as a source or target language, and focuses on lexical databases. The non-concatenative nature of Arabic morphology, the complex structure of Arabic word-forms, and the general use of vowel-free writing present a real challenge to NLP developers. We show here how and why a stem-grounded lexical d...

In this paper, we present the Arabic handwriting recognition system that was submitted to the 2013 NIST Open Handwriting Recognition and Translation Evaluation (OpenHaRT 2013). Our baseline recognition system is based on Hidden Markov Models and we also propose a lattice-based framework to combine the outputs from several different recognition engines. Keywords—Document recognition, Arabic hand...

This work is part of a big research project named "Oreillodule" aimed to develop tools for automatic speech recognition, translation, and synthesis for Arabic language. In this paper, our attention has mainly been focused on an attempt to present the semantic analyzer developed for the automatic comprehension of the standard spontaneous Arabic speech. We present a model of Arabic speech underst...